OpenRaiser/Intern-Atlas huggingface dataset:
Comparative Performance Analysis of Wireless Communication Protocols for Intelligent Sensors and Their Applications
Venue: arXiv cs.NI 2014
Year: 2014

The systems based on intelligent sensors are currently expanding, due to theirs functions and theirs performances of intelligence: transmitting and receiving data in real-time, computation and processing algorithms, metrology remote, diagnostics, automation and storage measurements...The radio frequency wireless communication with its multitude offers a better solution for data traffic in this kind of systems. The mains objectives of this paper is to present a solution of the problem related to the selection criteria of a better wireless communication technology face up to the constraints imposed by the intended application and the evaluation of its key features. The comparison between the different wireless technologies (Wi-Fi, Wi-Max, UWB, Bluetooth, ZigBee, ZigBeeIP, GSM/GPRS) focuses on their performance which depends on the areas of utilization. Furthermore, it shows the limits of their characteristics. Study findings can be used by the developers/ engineers to deduce the optimal mode to integrate and to operate a system that guarantees quality of communication, minimizing energy consumption, reducing the implementation cost and avoiding time constraints.
Defining UML Family Members Using Prefaces
Venue: arXiv cs.SE 2014
Year: 2014

The Unified Modeling Language is extensible, and so can be regarded as a family of languages. Implicitly or explicitly, any particular UML model should be accompanied by a definition of the particular UML family member used for the model. The definition should cover syntactic and semantic issues. This paper proposes a mechanism for associating models with such definitions. Any particular definition would form what we call a preface. The name is intended to suggest that the definition of a particular UML family member must conceptually come before any model built using that family member. A preface would be large, and should be organised using packages. This would allow large amounts of sharing between different prefaces. The paper proposes that prefaces should have an axiomatic style of semantics, through not necessarily fully formal, and it offers a general approach to semantics that would reduce problems of inconsistency within a large preface, based on the idea of general cases and special cases
Refinement of Information Flow Architectures
Venue: arXiv cs.SE 2014
Year: 2014

A calculus is presented for the stepwise refinement of abstract information flow architectures. We give a mathematical model for information flow components based on relations between input and output communication histories, and describe system architectures using two views: the glass box view is a network of basic components, while the black box view regards the network itself as a component. This allows us to hierarchically compose systems. The calculus consists of basic rules to add or remove components and channels, and to replace components by subnetworks and vice versa. The correctness of the rules is justified by the refinement relation on the black box view of architectures.
A manager's view on large scale XP projects
Venue: arXiv cs.SE 2014
Year: 2014

XP is a code oriented, light weight software engineering methodology, suited merely for small sized teams who develop software that relies on vague or rapidly changing requirements. Being very code oriented, the discipline of systems engineering knows it as approach of incremental system change. In this contribution, we discuss the enhanced version of a concept on how to extend XP on large scale projects with hundreds of software engineers and programmers, respectively. A previous version was already presented in [1]. The basic idea is to apply the "hierarchical approach", a management principle of reorganizing companies, as well as well known moderation principles to XP project organization. We show similarities between software engineering methods and company reorganization processes and discuss how the elements of the hierarchical approach can improve XP. We provide guidelines on how to scale up XP to very large projects e.g. those common in telecommunication industry and IT technology consultancy firms by using moderation techniques.
PCC: Re-architecting Congestion Control for Consistent High Performance
Venue: arXiv cs.NI 2014
Year: 2014

TCP and its variants have suffered from surprisingly poor performance for decades. We argue the TCP family has little hope to achieve consistent high performance due to a fundamental architectural deficiency: hardwiring packet-level events to control responses without understanding the real performance result of its actions. We propose Performance-oriented Congestion Control (PCC), a new congestion control architecture in which each sender continuously observes the connection between its actions and empirically experienced performance, enabling it to consistently adopt actions that result in high performance. We prove that PCC converges to a stable and fair equilibrium. Across many real-world and challenging environments, PCC shows consistent and often 10x performance improvement, with better fairness and stability than TCP. PCC requires no router hardware support or new packet format.
Multi-Dimensional and Non-Uniform Constellation Optimization via the Special Orthogonal Group
Venue: arXiv cs.IT 2014
Year: 2014

With the goal of optimizing the CM capacity of a finite constellation over a Rayleigh fading channel, we construct for all dimensions which are a power of 2 families of rotation matrices which optimize a certain objective function controlling the CM capacity. Our construction does not depend on any assumptions about the constellation, dimension, or signal-to-noise ratio. We confirm the benefits of our construction for uniform and non-uniform constellations at a large range of SNR values through numerous simulations. We show that in two and four dimensions one can obtain a further potential increase in CM capacity by jointly considering non-uniform and rotated constellations.
Reactive Programming for Interactive Graphics
Venue: arXiv cs.GR 2014
Year: 2014

One of the big challenges of developing interactive statistical applications is the management of the data pipeline, which controls transformations from data to plot. The user's interactions needs to be propagated through these modules and reflected in the output representation at a fast pace. Each individual module may be easy to develop and manage, but the dependency structure can be quite challenging. The MVC (Model/View/Controller) pattern is an attempt to solve the problem by separating the user's interaction from the representation of the data. In this paper we discuss the paradigm of reactive programming in the framework of the MVC architecture and show its applicability to interactive graphics. Under this paradigm, developers benefit from the separation of user interaction from the graphical representation, which makes it easier for users and developers to extend interactive applications. We show the central role of reactive data objects in an interactive graphics system, implemented as the R package cranvas, which is freely available on GitHub and the main developers include the authors of this paper.
Causal Graph Justifications of Logic Programs
Venue: arXiv cs.AI 2014
Year: 2014

In this work we propose a multi-valued extension of logic programs under the stable models semantics where each true atom in a model is associated with a set of justifications. These justifications are expressed in terms of causal graphs formed by rule labels and edges that represent their application ordering. For positive programs, we show that the causal justifications obtained for a given atom have a direct correspon- dence to (relevant) syntactic proofs of that atom using the program rules involved in the graphs. The most interesting contribution is that this causal information is obtained in a purely semantic way, by algebraic op- erations (product, sum and application) on a lattice of causal values whose ordering relation expresses when a justification is stronger than another. Finally, for programs with negation, we define the concept of causal stable model by introducing an analogous transformation to Gelfond and Lifschitz's program reduct. As a result, default negation behaves as "absence of proof" and no justification is derived from negative liter
Altruism in groups: an evolutionary games approach
Venue: arXiv cs.GT 2014
Year: 2014

We revisit in this paper the relation between evolution of species and the mathematical tool of evolutionary games, which has been used to model and predict it. We indicate known shortcoming of this model that restricts the capacity of evolutionary games to model groups of individuals that share a common gene or a common fitness function. In this paper we provide a new concept to remedy this shortcoming in the standard evolutionary games in order to cover this kind of behavior. Further, we explore the relationship between this new concept and Nash equilibrium or ESS. We indicate through the study of some example in the biology as Hawk and Dove game, Stag Hunt Game and Prisoner Dilemma, that when taking into account a utility that is common to a group of individuals, the equilibrium structure may change dramatically. We also study the multiple access control in slotted Aloha based wireless networks. We analyze the impact of the altruism behavior on the performance at the equilibrium.
A Deep Graph Embedding Network Model for Face Recognition
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we propose a new deep learning network "GENet", it combines the multi-layer network architec- ture and graph embedding framework. Firstly, we use simplest unsupervised learning PCA/LDA as first layer to generate the low- level feature. Secondly, many cascaded dimensionality reduction layers based on graph embedding framework are applied to GENet. Finally, a linear SVM classifier is used to classify dimension-reduced features. The experiments indicate that higher classification accuracy can be obtained by this algorithm on the CMU-PIE, ORL, Extended Yale B dataset.
Performance of Stanford and Minipar Parser on Biomedical Texts
Venue: arXiv cs.CL 2014
Year: 2014

In this paper, the performance of two dependency parsers, namely Stanford and Minipar, on biomedical texts has been reported. The performance of te parsers to assignm dependencies between two biomedical concepts that are already proved to be connected is not satisfying. Both Stanford and Minipar, being statistical parsers, fail to assign dependency relation between two connected concepts if they are distant by at least one clause. Minipar's performance, in terms of precision, recall and the F-score of the attachment score (e.g., correctly identified head in a dependency), to parse biomedical text is also measured taking the Stanford's as a gold standard. The results suggest that Minipar is not suitable yet to parse biomedical texts. In addition, a qualitative investigation reveals that the difference between working principles of the parsers also play a vital role for Minipar's degraded performance.
Extracting man-made objects from remote sensing images via fast level set evolutions
Venue: arXiv cs.CV 2014
Year: 2014

Object extraction from remote sensing images has long been an intensive research topic in the field of surveying and mapping. Most existing methods are devoted to handling just one type of object and little attention has been paid to improving the computational efficiency. In recent years, level set evolution (LSE) has been shown to be very promising for object extraction in the community of image processing and computer vision because it can handle topological changes automatically while achieving high accuracy. However, the application of state-of-the-art LSEs is compromised by laborious parameter tuning and expensive computation. In this paper, we proposed two fast LSEs for man-made object extraction from high spatial resolution remote sensing images. The traditional mean curvature-based regularization term is replaced by a Gaussian kernel and it is mathematically sound to do that. Thus a larger time step can be used in the numerical scheme to expedite the proposed LSEs. In contrast to existing methods, the proposed LSEs are significantly faster. Most importantly, they involve much fewer parameters while achieving better performance. The advantages of the proposed LSEs over other state-of-the-art approaches have been verified by a range of experiments.
Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study
Venue: arXiv cs.LG 2014
Year: 2014

This communication is devoted to solar irradiance and irradiation short-term forecasts, which are useful for electricity production. Several different time series approaches are employed. Our results and the corresponding numerical simulations show that techniques which do not need a large amount of historical data behave better than those which need them, especially when those data are quite noisy.
Coffman deadlocks in SCOOP
Venue: arXiv cs.PL 2014
Year: 2014

In this paper we address the deadlock detection problem in the context of SCOOP - an OO-programming model for concurrency, recently formalized in Maude. We present the integration of a deadlock detection mechanism on top of the aforementioned formalization and analyze how an abstract semantics of SCOOP based on a notion of "may alias expressions" can contribute to improving the deadlock detection procedure.
Experimental Demonstration of Nanosecond Accuracy Wireless Network Synchronization
Venue: arXiv cs.NI 2014
Year: 2014

Accurate wireless timing synchronization has been an extremely important topic in wireless sensor networks, required in applications ranging from distributed beam forming to precision localization and navigation. However, it is very challenging to realize, in particular when the required accuracy should be better than the runtime between the nodes. This work presents, to our knowledge for the first time, an experimental timing synchronization scheme that achieves a timing accuracy better than 5ns rms in a network with 4 nodes. The experimental hardware is built from commercially available components and based on software defined ultra wideband transceivers. The protocol for establishing the synchronization is based on our recently developed blink protocol that can scale from the small network demonstrated here to larger networks of hundreds or thousands of nodes.
Using 3D Printing to Visualize Social Media Big Data
Venue: arXiv cs.GR 2014
Year: 2014

Big data volume continues to grow at unprecedented rates. One of the key features that makes big data valuable is the promise to find unknown patterns or correlations that may be able to improve the quality of processes or systems. Unfortunately, with the exponential growth in data, users often have difficulty in visualizing the often-unstructured, non-homogeneous data coming from a variety of sources. The recent growth in popularity of 3D printing has ushered in a revolutionary way to interact with big data. Using a 3D printed mockup up a physical or notional environment, one can display data on the mockup to show real-time data patterns. In this poster and demonstration, we describe the process of 3D printing and demonstrate an application of displaying Twitter data on a 3D mockup of the Massachusetts Institute of Technology (MIT) campus, known as LuminoCity.
Context-Based Information Retrieval in Risky Environment
Venue: arXiv cs.IR 2014
Year: 2014

Context-Based Information Retrieval is recently modelled as an exploration/ exploitation trade-off (exr/exp) problem, where the system has to choose between maximizing its expected rewards dealing with its current knowledge (exploitation) and learning more about the unknown user's preferences to improve its knowledge (exploration). This problem has been addressed by the reinforcement learning community but they do not consider the risk level of the current user's situation, where it may be dangerous to explore the non-top-ranked documents the user may not desire in his/her current situation if the risk level is high. We introduce in this paper an algorithm named CBIR-R-greedy that considers the risk level of the user's situation to adaptively balance between exr and exp.
Global Information Sharing under Network Dynamics
Venue: arXiv cs.DC 2014
Year: 2014

We study how to spread $k$ tokens of information to every node on an $n$-node dynamic network, the edges of which are changing at each round. This basic {\em gossip problem} can be completed in $O(n + k)$ rounds in any static network, and determining its complexity in dynamic networks is central to understanding the algorithmic limits and capabilities of various dynamic network models. Our focus is on token-forwarding algorithms, which do not manipulate tokens in any way other than storing, copying and forwarding them. We first consider the {\em strongly adaptive} adversary model where in each round, each node first chooses a token to broadcast to all its neighbors (without knowing who they are), and then an adversary chooses an arbitrary connected communication network for that round with the knowledge of the tokens chosen by each node. We show that $Ω(nk/\log n + n)$ rounds are needed for any randomized (centralized or distributed) token-forwarding algorithm to disseminate the $k$ tokens, thus resolving an open problem raised in~\cite{kuhn+lo:dynamic}. The bound applies to a wide class of initial token distributions, including those in which each token is held by exactly one node and {\em well-mixed} ones in which each node has each token independently with a constant probability. We also show several upper bounds in varying models.
Maximum mutual information regularized classification
Venue: arXiv cs.LG 2014
Year: 2014

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reduc- ing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradi- ent descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.
Community Detection via Local Dynamic Interaction
Venue: arXiv cs.SI 2014
Year: 2014

How can we uncover the natural communities in a real network that allows insight into its underlying structure and also potential functions? In this paper, we introduce a new community detection algorithm, called Attractor, which automatically spots the communities or groups in a network over time via local dynamic interaction. The basic idea is to envision a network as a dynamical system, and each agent interacts with its local partners. Instead of investigating the node dynamics, we actually examine the change of "distances" among linked nodes. As time evolves, these distances will be shrunk or stretched gradually based on their topological structures. Finally all distances among linked nodes will converge into a stable pattern, and communities can be intuitively identified. Thanks to the dynamic viewpoint of community detection, Attractor has several potential attractive properties: (a) Attractor provides an intuitive solution to analyze the community structure of a network, and faithfully captures the natural communities (with high quality). (b) Owing to its time complexity $O(|E|)$, Attractor allows finding communities on large networks. (c) The small communities or anomalies, usually existing in real-world networks, can be well pinpointed. (d) Attractor is easy to parameterize, since there is no need to specify the number of clusters. Extensive experiments on synthetic and real-world networks further demonstrate the effectiveness and efficiency of the proposed approach.
Weighted Shortest Path Models: A Revisit to the Simulation of Internet Routing
Venue: arXiv cs.NI 2014
Year: 2014

Understanding how packets are routed in Internet is significantly important to Internet measurement and modeling. The conventional solution for route simulation is based on the assumption of unweighted shortest path. However, it has been found and widely accepted that a packet in Internet is usually not transmitted along the unweighted shortest path between its source and destination. To better simulate the routing behavior of a packet, we thoroughly explore the real-world Internet routes and present a novel local information based simulation model, with a tuning parameter, which assigns weights to links based on local information and then simulates the Internet route with weighted shortest path. Comparisons with baseline approaches show its capability in well replicating the route length distribution and other structural properties of the Internet topology. Meanwhile, the optimal parameter of this model locates in the range of (0, 2), which implies that a packet inside the Internet inclines to move to nodes with small degrees. This behavior actually reflects the design philosophy of Internet routing, balancing between network efficiency and traffic congestion.
Reaching Consensus Among Mobile Agents: A Distributed Protocol for the Detection of Social Situations
Venue: arXiv cs.SI 2014
Year: 2014

Physical social encounters are governed by a set of socio-psychological behavioral rules with a high degree of uniform validity. Past research has shown how these rules or the resulting properties of the encounters (e.g. the geometry of interaction) can be used for algorithmic detection of social interaction. In this paper, we present a distributed protocol to gain a common understanding of the existing social situations among agents. Our approach allows a group of agents to combine their subjective assessment of an ongoing social situation. Based on perceived social cues obtained from raw data signals, they reach a consensus about the existence, parameters, and participants of a social situation. We evaluate our protocol using two real-world datasets with social interaction information and additional synthetic data generated by our social-aware mobility model.
Full abstraction for fair testing in CCS (expanded version)
Venue: arXiv cs.LO 2014
Year: 2014

In previous work with Pous, we defined a semantics for CCS which may both be viewed as an innocent form of presheaf semantics and as a concurrent form of game semantics. We define in this setting an analogue of fair testing equivalence, which we prove fully abstract w.r.t. standard fair testing equivalence. The proof relies on a new algebraic notion called playground, which represents the `rule of the game'. From any playground, we derive two languages equipped with labelled transition systems, as well as a strong, functional bisimulation between them.